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Numerical recipes in C (2nd ed.): the art of scientific computing
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Artificial Intelligence - Special volume on computer vision
A volumetric method for building complex models from range images
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The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
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International Journal of Computer Vision
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Curvature-Augmented Tensor Voting for Shape Inference from Noisy 3D Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Match Propogation for Image-Based Modeling and Rendering
IEEE Transactions on Pattern Analysis and Machine Intelligence
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ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Automatic Camera Recovery for Closed or Open Image Sequences
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Complete Dense Stereovision Using Level Set Methods
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
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Surviving Dominant Planes in Uncalibrated Structure and Motion Recovery
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
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SMILE '00 Revised Papers from Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Euclidean Reconstruction from Uncalibrated Views
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Photorealistic Scene Reconstruction by Voxel Coloring
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Autocalibration and the absolute quadric
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Fast Surface Reconstruction Using the Level Set Method
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Accurate Camera Calibration for Off-line, Video-Based Augmented Reality
ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
Gauge freedoms and uncertainty modeling for three-dimensional computer vision
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ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Constructing Virtual Worlds Using Dense Stereo
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Surface Reconstruction by Integrating 3D and 2D Data of Multiple Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Dense Matching of Multiple Wide-baseline Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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ACM SIGGRAPH 2005 Papers
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Parisian evolution with honeybees for three-dimensional reconstruction
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Implementation of modeling hair from multiple views
SIGGRAPH '05 ACM SIGGRAPH 2005 Sketches
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IEEE Transactions on Pattern Analysis and Machine Intelligence
A random sampling strategy for piecewise planar scene segmentation
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Video-object segmentation and 3D-trajectory estimation for monocular video sequences
Image and Vision Computing
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Image and Vision Computing
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ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
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Computer Vision and Image Understanding
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This paper proposes a quasi-dense approach to 3D surface model acquisition from uncalibrated images. First, correspondence information and geometry are computed based on new quasi-dense point features that are resampled subpixel points from a disparity map. The quasi-dense approach gives more robust and accurate geometry estimations than the standard sparse approach. The robustness is measured as the success rate of full automatic geometry estimation with all involved parameters fixed. The accuracy is measured by a fast gauge-free uncertainty estimation algorithm. The quasi-dense approach also works for more largely separated images than the sparse approach, therefore, it requires fewer images for modeling. More importantly, the quasi-dense approach delivers a high density of reconstructed 3D points on which a surface representation can be reconstructed. This fills the gap of insufficiency of the sparse approach for surface reconstruction, essential for modeling and visualization applications. Second, surface reconstruction methods from the given quasi-dense geometry are also developed. The algorithm optimizes new unified functionals integrating both 3D quasi-dense points and 2D image information, including silhouettes. Combining both 3D data and 2D images is more robust than the existing methods using only 2D information or only 3D data. An efficient bounded regularization method is proposed to implement the surface evolution by level-set methods. Its properties are discussed and proven for some cases. As a whole, a complete automatic and practical system of 3D modeling from raw images captured by hand-held cameras to surface representation is proposed. Extensive experiments demonstrate the superior performance of the quasi-dense approach with respect to the standard sparse approach in robustness, accuracy, and applicability.